Variational learning of a Dirichlet process of generalized Dirichlet distributions for simultaneous clustering and feature selection
W Fan, N Bouguila - Pattern Recognition, 2013 - Elsevier
This paper introduces a novel enhancement for unsupervised feature selection based on
generalized Dirichlet (GD) mixture models. Our proposal is based on the extension of the …
generalized Dirichlet (GD) mixture models. Our proposal is based on the extension of the …
ICFS clustering with multiple representatives for large data
With the prevailing development of Cyber-physical-social systems and Internet of Things,
large-scale data have been collected consistently. Mining large data effectively and …
large-scale data have been collected consistently. Mining large data effectively and …
A Bayesian reliability evaluation method with different types of data from multiple sources
L Wang, R Pan, X Wang, W Fan, J Xuan - Reliability Engineering & System …, 2017 - Elsevier
Abstract Bernoulli data (pass/fail), lifetime data, and degradation data are commonly
encountered in product reliability assessment. Oftentimes these data are collected from …
encountered in product reliability assessment. Oftentimes these data are collected from …
Unsupervised anomaly intrusion detection via localized bayesian feature selection
In recent years, an increasing number of security threats have brought a serious risk to the
internet and computer networks. Intrusion Detection System (IDS) plays a vital role in …
internet and computer networks. Intrusion Detection System (IDS) plays a vital role in …
Learning deep features for DNA methylation data analysis
Z Si, H Yu, Z Ma - IEEE Access, 2016 - ieeexplore.ieee.org
Many studies demonstrated that the DNA methylation, which occurs in the context of a CpG,
has strong correlation with diseases, including cancer. There is a strong interest in analyzing …
has strong correlation with diseases, including cancer. There is a strong interest in analyzing …
A benchmark dataset and learning high-level semantic embeddings of multimedia for cross-media retrieval
The selection of semantic concepts for modal construction and data collection remains an
open research issue. It is highly demanding to choose good multimedia concepts with small …
open research issue. It is highly demanding to choose good multimedia concepts with small …
Bayesian estimation of generalized gamma mixture model based on variational em algorithm
In this paper, we propose a Bayesian inference method for the generalized Gamma mixture
model (GΓMM) based on variational expectation-maximization algorithm. Specifically, the …
model (GΓMM) based on variational expectation-maximization algorithm. Specifically, the …
Online learning of a dirichlet process mixture of beta-liouville distributions via variational inference
W Fan, N Bouguila - IEEE transactions on neural networks and …, 2013 - ieeexplore.ieee.org
A large class of problems can be formulated in terms of the clustering process. Mixture
models are an increasingly important tool in statistical pattern recognition and for analyzing …
models are an increasingly important tool in statistical pattern recognition and for analyzing …
Intelligent VNFs selection based on traffic identification in vehicular cloud networks
J Wang, B He, J Wang, T Li - IEEE Transactions on Vehicular …, 2018 - ieeexplore.ieee.org
Internet of Vehicles (IoV) has become a significant research area due to its specific features
and applications such as efficient traffic management, road safety, and entertainment …
and applications such as efficient traffic management, road safety, and entertainment …
Unsupervised hybrid feature extraction selection for high-dimensional non-gaussian data clustering with variational inference
Clustering has been a subject of extensive research in data mining, pattern recognition, and
other areas for several decades. The main goal is to assign samples, which are typically non …
other areas for several decades. The main goal is to assign samples, which are typically non …